Intra- and inter-tumor heterogeneity in a vemurafenib-resistant melanoma patient and derived xenografts.

The development of targeted inhibitors, like vemurafenib, has greatly improved the clinical outcome of BRAF(V600E) metastatic melanoma. However, resistance to such compounds represents a formidable problem. Using whole-exome sequencing and functional analyses, we have investigated the nature and pleiotropy of vemurafenib resistance in a melanoma patient carrying multiple drug-resistant metastases. Resistance was caused by a plethora of mechanisms, all of which reactivated the MAPK pathway. In addition to three independent amplifications and an aberrant form of BRAF(V600E), we identified a new activating insertion in MEK1. This MEK1(T55delins) (RT) mutation could be traced back to a fraction of the pre-treatment lesion and not only provided protection against vemurafenib but also promoted local invasion of transplanted melanomas. Analysis of patient-derived xenografts (PDX) from therapy-refractory metastases revealed that multiple resistance mechanisms were present within one metastasis. This heterogeneity, both inter- and intra-tumorally, caused an incomplete capture in the PDX of the resistance mechanisms observed in the patient. In conclusion, vemurafenib resistance in a single patient can be established through distinct events, which may be preexisting. Furthermore, our results indicate that PDX may not harbor the full genetic heterogeneity seen in the patient's melanoma.

High sensitivity of cancer exome-based CD8 T cell neo-antigen identification.

Recent data suggest that T-cell reactivity against tumor-specific neo-antigens may be central to the clinical efficacy of cancer immunotherapy. The development of personalized vaccines designed to boost T-cell reactivity against patient specific neo-antigens has been proposed largely on the basis of these findings. Work from several groups has demonstrated that novel tumor-specific antigens can be discovered through the use of cancer exome sequencing data, thereby providing a potential pipeline for the development of patient-specific vaccines. Importantly though, it has not been established which fraction of cancer neo-antigens that can be recognized by CD8+ T cells is successfully uncovered with the current exome-based epitope prediction strategies. Here, we use a data set comprising human cancer neo-antigens that was previously identified through the use of unbiased, computational-independent strategies to describe the potential of cancer exome-based neo-antigen discovery. This analysis shows a high sensitivity of exome-guided neo-antigen prediction of approximately 70%. We propose that future research should focus on the analysis and optimization of the specificity of neo-antigen prediction, and should undoubtedly entail the clinical evaluation of patient-specific vaccines with the aim of inducing immunoreactivity against tumor-displayed neo-antigens in a physiologically relevant context.